This invention relates generally to radar and sonar processing systems, and more particularly, to pulse compression processing systems utilizing sampling techniques.
Pulse compression techniques are frequently utilized in radar and sonar systems in order to transmit long pulses with a large energy content so as to obtain both good detection capability (range) and good range resolution. In the operation of a conventional pulse compression system, the carrier frequency of a transmitter is varied linearly or in a step-wise approximation to linear over a frequency bandwidth B, which defines the basic signal information bandwidth. When a target reflected echo is received, this signal may be processed through a matched filter which compresses the target reflected pulse into a relatively short pulse. This target reflected pulse may be compressed up to 1/B. Such matched filter processing is implemented by correlating each received signal with the signal transmitted such that a short compressed pulse is obtained at the point of optimum correlation. This compressed pulse will be accompanied by spurious responses commonly referred to as range or time sidelobes on either side thereof. High range-time sidelobes not only decrease the sensitivity of the system but also allow big targets with large sidelobes to effectively mask smaller targets, i.e. an aircraft with a large cross-section could effectively mask a missile of much smaller cross-section. Accordingly, a prime concern in the reflected signal processing art is the reduction of such sidelobes.
It is known in the art that digital-type processing yields quite low range-time sidelobes. It has been found that the sampling of the target echo signal at the Nyquist rate for the information baseband yields the lowest sidelobe ratio (generally on the order of 30 dB). The Nyquist rate is defined as twice the information bandwidth B or, where in-phase (I) and quadrature (Q) reference frame signals are used, it is the same as the information bandwidth. The signal samples resulting from the sampling operation are passed through a discrete or digital correlator that compares them with the transmitted waveform and produces an output which is the autocorrelation function of the transmitted waveform. This autocorrelation function will have a maximum value when the sampling begins at the beginning of the incoming target-echo signal. However, when the target-echo leading edge arrives halfway between samples, then the maximum of the autocorrelation function is significantly reduced. The target echo signal energy is essentially spread over two or more sampling periods or range cells resulting in a flattened maximum mainlobe with a lower mainlobe to sidelobe ratio. Thus, such a half sampling period error yields a significant range resolution loss and a decrease in radar sensitivity. As noted above, such spreading of the mainlobe is especially detrimental because it allows large cross-section targets to effectively mask smaller targets.
In order to avoid such sampling error losses, pulse compressor samplers generally operate at much higher rates than the optimum Nyquist rate in order to reduce the possible delay error between the start of a sampling period and the arrival of the leading edge of the target echo signal. However, such high sampling rates increase the range-time sidelobes in radar and sonar systems utilizing linear or step approximation to linear frequency modulation waveforms such that the autocorrelation response approaches a (sin X) X falloff, i.e. the mainlobe to sidelobe ratio approaches 13 dB. The resulting high sidelobes force designers to amplitude weight the frequency spectrum of the received target-echo signal in order to obtain a sidelobe reduction. This spectrum weighting, in essence, removes energy from certain frequencies in the return-echo pulse thereby tapering the frequency spectrum of the pulse with attendant sidelobe reduction. However, such spectrum tapering also reduces the bandwidth of the target echo signal. But, since the transmitter bandwidth remains unchanged, the receiver bandwidth is no longer matched to the signal bandwidth resulting in a reduced signal-to-noise ratio. Accordingly, such weighting reintroduces sensitivity loss and reduces the energy efficiency of the system.